Enhanced optical coherence tomography for anatomical mapping

ABSTRACT

A system, method and apparatus for anatomical mapping utilizing optical coherence tomography. In the present invention, 3-dimensional fundus intensity imagery can be acquired from a scanning of light back-reflected from an eye. The scanning can include spectral domain scanning, as an example. A fundus intensity image can be acquired in real-time. The 3-dimensional data set can be reduced to generate an anatomical mapping, such as an edema mapping and a thickness mapping. Optionally, a partial fundus intensity image can be produced from the scanning of the eye to generate an en face view of the retinal structure of the eye without first requiring a full segmentation of the 3-D data set. Advantageously, the system, method and apparatus of the present invention can provide quantitative three-dimensional information about the spatial location and extent of macular edema and other pathologies. This three-dimensional information can be used to determine the need for treatment, monitor the effectiveness of treatment and identify the return of fluid that may signal the need for re-treatment.

PRIORITY

This application claims the benefit of the filing date under 35 U.S.C. §119(e) of U.S. Provisional Patent Application Ser. No. 60/632,387, filedon Dec. 2, 2004, which is hereby incorporated by reference in itsentirety.

BACKGROUND OF THE INVENTION

1. Technical Field

The present invention relates to coherent waveform based imaging, andmore particularly to an optical coherence tomography (OCT) imagingsystem.

2. Statement of the Related Art

Many imaging systems utilize coherent waveforms to obtain informationregarding target objects of interest. Examples include OCT, ultrasounddiagnostics, and synthetic aperture radar. OCT is a low-coherenceinterferometer-based noninvasive medical imaging modality that canprovide high-resolution sectional images of biological tissues (see forexample, U.S. Pat. No. 5,321,501, U.S. Pat. No. 5,459,570, Huang, D. etal. (1991). “Optical coherence tomography.” Science 254(5035): 1178-81).Since first introduced, OCT has been used in a variety of medicalresearch and diagnostic applications. One successful application of OCTimagery can include the use of OCT in the dermatological imaging of theskin. Another successful application of OCT imagery can includesectional imaging of the retina in the field of ophthalmology. In thisregard, time domain based OCT has produced cross-sectional images of theretina of the eye that have proven value to ophthalmologists (see forexample, Swanson, E. A. et al. (1993). “In-vivo retinal imaging byoptical coherence tomography.” Optics Letters 18(21): 1864-1866; Izatt,J. A. et al. (1993). “Ophthalmic diagnostics using optical coherencetomography”. Ophthalmic Technologies III, SPIE, 1877: 136-144, LosAngeles, Calif., USA). Notwithstanding, time domain OCT instrumentscannot acquire sufficient data to characterize completely importantretinal pathologies.

The limitations of time domain OCT are the natural result of theinherent difficulties in acquiring and processing imagery of an unstabletarget—the human eye. For example, although ophthalmic OCT has beencommercialized for several years, the spatial registration of an OCTimage to fundus landmarks has not been achieved satisfactorily. In thisregard, fundus landmarks can be used to relate different structuralabnormalities at different retinal locations. Precise spatialregistration of OCT sections to tissue location also can be importantwhen interpreting other medical images. Yet, the unavoidable eyemovement of a patient during image acquisition can complicate theability to achieve precise spatial registration due to the unavoidabledistortion of the OCT image.

As an alternative to OCT, the scanning laser ophthalmoscope (SLO)provides en face fundus images familiar to ophthalmologists (see forexample, Sharp, P. F. et al (2004) “The scanning laser ophthalmoscope—areview of its role in bioscience and medicine” Physics in Medicine andBiology 49: 1085-1096). In this regard, en face views are familiar toophthalmologists not only from direct observations, but also from fundusphotographs and fluorescein angiography. The strength of an en face viewis that structural abnormalities at different retinal locations can berelated to each other and to major retinal landmarks such as the foveaand optic nerve head. In any case, combining OCT with SLO (SLO/OCT)provides one possible means for precise spatial registration of the OCTimage while providing an en face fundus image (see for example, U.S.Pat. No. 5,975,697, U.S. Pat. No. 6,769,769, CA2390072, US20040036838,US20040233457, and WO2004102112).

Specifically, time domain SLO/OCT systems utilize two-dimensionaltransverse scans to provide sectional images in planes perpendicular tothe depth of the sample. In an SLO/OCT system, the fundus image can beacquired by splitting the reflected sample light during the transversescan into two detection channels. A first channel can accommodate OCTwhile the second channel can be utilized in acquiring intensity image(see for example, U.S. Pat. No. 5,975,697, U.S. Pat. No. 6,769,769,CA2390072, US20040036838, US20040233457, and WO2004102112). As analterative approach, the sectional images can be summed along the depthof the image (see for example, Hitzenberger, C. K. et al. (2003).“Three-dimensional imaging of the human retina by high-speed opticalcoherence tomography.” Optics Express 11(21): 2753-2761; Puliafito C. A.“Summary and Significance” American Academy of OphthalmologySubspecialty Day on retina, Section X: Ocular Imaging, New Orleans, Oct.23, 2004, 3:06 pm). The approach of two detection channels can require amore complicated setup and the signal-to-noise ratio of the OCT may bereduced by a partial sacrifice of the back-reflected sample light. Bycomparison, in the approach of summing the OCT images along their depth,accuracy can be sacrificed when the eye moves between differentsections.

SUMMARY OF THE INVENTION

The present invention is an OCT method, system and apparatus whichaddresses the foregoing deficiencies of time domain ocular imaging. Inparticular, what is provided is a novel method, system and apparatus foranatomical mapping using spectral domain OCT. As well, time-domain OCTand swept source frequency OCT also can be applied to provide theenhanced anatomical mapping of the present invention. In this invention,the term spectral domain OCT (SD-OCT) is sometimes used to include bothspectrometer based spectral or Fourier domain OCT, and tunable laserbased swept source OCT since their basic principle of operation is verysimilar (see for example, Choma, M. A. et al. (2003). “Sensitivityadvantage of swept source and Fourier domain optical coherencetomography.” Optics Express 11(18): 2183-2189). In accordance with thepresent invention, a fundus intensity image can be acquired from aspectral domain scanning of light back-reflected from an eye. The term“intensity image” as defined in this invention is a two-dimensionalen-face image extracted from a 3D OCT data block by integrating the OCTsignal over a depth range (Z-axis) greater than the axial resolution ofthe OCT system. For example, a fundus image can be extracted by themethod disclosed herein from OCT data covering the fundus of the humaneye. The fundus intensity image actually represents a reduction in totalinformation content. Specifically, the squaring and summing over thespectra results in a loss of all depth information. Yet, the loss ofdepth information can achieve a shortcut to a particularly useful itemof distilled information for the purpose of medical diagnostics.

A 3-D OCT data set can be reduced to generate an ocular mapping,including edema mappings and thickness mappings. Optionally, a partialfundus intensity image can be produced from the spectral domain scanningof the eye to generate an en face view of the retinal structure of theeye without first requiring a full segmentation of the 3-D OCT data. Thepartial intensity image is a two-dimensional en-face image extractedfrom a 3D OCT data block by integrating the OCT signal over a depthrange greater than the axial resolution of the OCT system, but includingonly selected regions of the 3-D anatomical structure for integration.

The present invention can differ from conventional, time domain OCTtechnology because the mapping system of the present invention can beoptimized to obtain the information necessary for assessing macularedema while simultaneously producing a fundus intensity image. As partof the optimization, the present invention utilizes optimized samplinggrids. For example, in the case of volume measurements of fluid-filledspaces, which require several samples spread over the areal extent ofthe space, a raster scan can be utilized having evenly spaced points ona square grid.

Importantly, in accordance with the present invention, the data setacquired by the spectral domain scan can contain all of the 3-Dinformation about retinal structure needed to estimate the volumes offluid-filled spaces. Accordingly, 3-D segmentation algorithms can beapplied to the intensity data set to outline spatial structures. As yetanother important aspect of the invention, intensity information can beextracted from each measured spectrum to provide an en face view or animage of the fundus that can be used immediately to judge image dataquality. In this regard, an operator can then decide whether or not totake another image. Because the intensity image is generated from thesame data as the subsequent 3-D data set, the intensity image providesall necessary landmarks for precisely locating on the fundus the lesionsrevealed by the cross-sectional OCT scan. The intensity image alsoprovides the landmarks needed for orienting the 3-D data set to otherfundus images, such as fundus photographs and fluorescein angiograms.

As an additional advantage, because the fundus intensity image can begenerated before segmentation of the 3-D data set, the fundus intensityimage can be used to guide the segmentation. For example, retinal bloodvessels represent discontinuities in the layered retinal architecturethat often disrupt segmentation of cross-sectional images. The fundusintensity image can be processed by ordinary 2-D algorithms to identifythe blood vessel positions. Subsequent processing of the OCTcross-sectional images then can be modified at each vessel location. Forinstance, an algorithm designed to follow layers can skip past a vesseland resume segmentation on the other side of the vessel. Additionalaspects of the invention will be set forth in part in the descriptionwhich follows, and in part will be obvious from the description, or maybe learned by practice of the invention. The aspects of the inventionwill be realized and attained by means of the elements and combinationsparticularly pointed out in the appended claims. It is to be understoodthat both the foregoing general description and the following detaileddescription are exemplary and explanatory only and are not restrictiveof the invention, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of the present invention, and theattendant advantages and features thereof, will be more readilyunderstood by reference to the following detailed description whenconsidered in conjunction with the accompanying drawings, wherein:

FIG. 1 is a schematic illustration of an OCT imaging system configuredfor anatomical mapping in accordance with the present invention; and,

FIG. 2 is a flow chart illustrating a process for anatomical mapping inthe OCT imaging system of FIG. 1.

DETAILED DESCRIPTION OF THE INVENTION

The present invention is a system, method and apparatus for anatomicalmapping through the production of a 3-D data set, for instance throughimagery produced utilizing OCT. In accordance with the presentinvention, a fundus intensity image can be acquired from a spectraldomain scanning of light back-reflected from an eye. The 3-D data setcan be reduced to generate an ocular mapping, including edema mappingsand thickness mappings. Optionally, a partial fundus intensity image canbe produced from the spectral domain scanning of the eye to generate anen face view of the retinal structure of the eye without first requiringa full segmentation of the 3-D data set.

In further illustration, FIG. 1 is a schematic illustration of an OCTimaging system configured for anatomical mapping in accordance with thepresent invention. As shown in FIG. 1, a low coherent light source 105can be provided. The low coherent light source 105 can be asuper-luminescent diode, such as a super-luminescent diode having acenter wavelength sufficient to penetrate the vitreous portions of theeye 140—typically between 800 and 900 nm. In this context, those skilledin the art consider such a light source as a broadband light source. Thelight source 105 can be coupled to a beam splitter 115 by way ofoptional fiber-based isolator 110.

Specifically, the beam splitter 115 can be a 2×2 3 dB fiber couplerconfigured to split light emanating from the light source 105 intosample and reference arms. The sample arm can be coupled into theoptical head of a light delivery system 165. The light delivery system165 can include an x-y scanner 130 and optics for delivering the samplelight into the eye 140 and collecting the back-reflected sample light.Optionally, the back-reflected sample light can be partially reflectedthrough operation of a dichroic mirror 135 into a video camera 145 forreal time viewing of the fundus.

By comparison to the sample arm, the reference arm can include avariable neutral density filter 125 used to adjust the referenceintensity before and after the light reaches the optical referencesystem 170. Polarization controllers 120 can be used in both thereference and sample arms for fine tuning of the sample and referencepolarization states to achieve maximal interference. In an exemplaryconfiguration of the detection arm, a spectrometer 160 can be coupled toa line scan camera 155 to detect the combined reference and samplelight. As is known in the art, a spectrometer will include an opticalelement such as a diffraction grating for angularly dispersing the lightas a function of wavelength. The dispersed light falls on the pixels ofthe line scan camera. The light intensities measured by the camerapixels contain information corresponding to the distribution ofreflection sites along the Z-axis depth in the sample.

Both the line scan camera 155 and the video camera 145 can becommunicatively linked to a computer 150. The computer 150 can becoupled both to a data acquisition processor 190 configured to acquiredata from the line scan camera 155, and also to a data reductionprocessor 195 configured to reduce the acquired data to produceanatomical maps 185A and partial fundus imagery 185B. The 3-D data setswould also be used to create cross-sectional OCT images 185C as known inthe art.

By operation of the data acquisition processor 190, both a 3-D data set180 and an intensity image 175 can be acquired. The intensity image 175can be acquired in real time directly from the data acquisitionprocessor using either digital or analog processing. Complex dataprocessing associated with generating OCT images is not required.Consequently, an operator can discard the image if it is determined thatthe image is of too low quality without permitting further dataprocessing. The 3-D data set 180, by comparison, can be produced byoperation of the data reduction processor 195 from the image acquired bythe data acquisition process 190. Notably, an intensity image 175 canalso be derived from the 3-D data set. An intensity image created eitherdirectly from the data acquisition or from the 3-D data set can beuseful for data registration to other imaging modalities. Moreover,blood vessels can be identified as an initial step in a segmentationprocess. In a swept source spectral domain OCT embodiment, the outputwavelength of the light source can be varied or scanned, for example,via frequency modulation. Only a single photodetector is required ratherthan a spectrometer and a line scan camera. The intensity data as afunction of wavelength is extracted over time.

In a more particular illustration, FIG. 2 is a flow chart illustrating aprocess for anatomical mapping in the OCT imaging system of FIG. 1.Beginning first in block 210, the inherent speed of a spectral domainOCT can be utilized to sample the entire macula of an eye on a squaregrid. In a specific aspect of the invention, a total of 65,536 a-scanscan be collected in slightly over one second by following aleft-to-right, top-to-bottom scan pattern in which adjacent a-scans areseparated by 23 μm, which provides adequate lateral resolution to samplefluid-filled spaces of the eye.

In block 220, a fundus image can be generated directly from intensitydata included within the spectra produced by the spectral domain scan.In this regard, it is to be noted that each captured spectrum containsat least two components from which can be extracted a signalproportional to the total reflected intensity. This intensity signal canbe used to produce a 2-D image of the fundus that advantageously canappear similar to the image from an SLO. Various methods can be employedto obtain the intensity signal in “real-time”, so that the fundus imagecan be painted on a display screen as rapidly as it is acquired.

The method for extracting intensity information can be understood byconsidering the primary mathematical expression for the spectralintensity of the interference fringes falling on the line scan camera:${{G_{d}(v)} = {{G_{s}(v)}\{ {1 + {\sum\limits_{n}R_{sn}} + {2{\sum\limits_{n \neq m}{\sqrt{R_{sn}R_{sm}}{\cos\lbrack {2\pi\quad{v( {\tau_{n} - \tau_{m}} )}} \rbrack}}}} + {2{\sum\limits_{n}{\sqrt{R_{sn}}{\cos\lbrack {2\pi\quad{v( {\tau_{n} - \tau_{r}} )}} \rbrack}}}}} \}}},$where v is the frequency of the light; R_(sn) is the intensityreflection of a small region in the sample; G_(s)(v) is the spectraldensity of the light source; the reflection of the reference arm isunity; distances are represented by propagation times τ_(n), τ_(m) inthe sample arm and τ_(r) in the reference arm and summation is acrossall axial depths in the sample beam. The third term in brackets is themutual interference for all light scattered within the sample and thelast term contains the interference between the scattered sample lightand the reference light from which an a-scan is calculated. It isimportant to note that, in embodiments where the detector is aspectrometer, the parameter v also represents position on the line scancamera. Hence, the primary equation can be broken conceptually into twoparts: the first two terms represent slow variation across the lineararray of camera pixels while the last two terms represent oscillations(interference fringes). Similarly, in the embodiments where the sourceis swept through a range of frequencies v the first two terms in theprimary equation represent slow variation in time of the detectedsignal, while the last two terms represent oscillations.

The new insight that leads to generation of a fundus image is torecognize that the desired information about total reflected sampleintensity resides in both the second and fourth terms of the primaryequation. This permits multiple methods for extracting the intensity.The method selected for a particular application will depend on desiredspeed and accuracy. Several examples of methodologies for obtaining afundus intensity image follow in which F(x,y) is the output of theprocessing method for an a-line at scan point x,y on the fundus.

In a first example, the primary equation can be summed across v (inpractice, across the pixels of the line scan camera). Notably, thecosine terms in the primary equation which have many cycles across thespectrum will sum to (approximately) zero. Thus, applying the summationcan yield${{F( {x,y} )} = {{\overset{\_}{G}}_{s}( {1 + {\sum\limits_{n}R_{sn}}} )}},$where {overscore (G)}_(s) is the total source power. The first term can,in principle, be ignored for display purposes leaving${\sum\limits_{n}R_{sn}},$which is proportional to the sum of all reflected intensities in thesample, i.e., the desired fundus intensity. Digital summation of thecamera output can be very fast and this method may be most suitable forpainting the fundus image into a display window as rapidly as it isacquired. Various techniques can be used, if necessary, to compensatefor small variations in {overscore (G)}_(s) with x,y. It is clear thatother low-pass filter techniques besides simple summation can also beapplied to the primary equation to yield the above result.

In another example, the fundus intensity can also be derived from thefourth term of the primary equation by separating the oscillatorycomponent from the slow variation and recognizing that, for retina andother low reflectance samples, the third term is small relative to thefourth term. One method to achieve this is to apply a Fourier transformto the primary equation, to discard the low frequency terms, and then tosquare and sum the high frequency terms. By Parseval's theorem this isequivalent in the camera output signal to high pass filtering theprimary equation to remove the low frequency component, then squaringthe remaining oscillatory component and summing over the spectrum.

Neglecting the third term of the equation, the high pass filtering,squaring and summing of the primary equation can produce:${{F( {x,y} )} = {{\sum\limits_{v}\{ {2{\sum\limits_{n}{\sqrt{R_{sn}}{G_{s}(v)}{\cos\lbrack {2\pi\quad{v( {\tau_{n} - \tau_{r}} )}} \rbrack}}}} \}^{2}} = {4{\overset{\_}{G}}_{s}^{2}{\sum\limits_{n}R_{sn}}}}},$which can be displayed directly to produce an intensity image. It isnoted that one can modify the parameters of the high-pass filter inorder to change the contrast of the fundus image by changing therelative contributions of shallower and deeper structures. The choice ofdomain in which to operate depends on considerations of speed and easeof implementation. Operations on the camera output can be carried outdigitally or, for highest speed, by analog processing. Similarly, in athird exemplary method for obtaining a fundus intensity image, theobservation that a spectrometer normally discards the zero order beamcan be utilized such that the intensity of the zero order beam also canhave the form of the equation yielded by the summation of the primaryequation. Thus, the intensity signal can be obtained directly with anauxiliary photodetector and displayed with conventional methods.

Returning now to FIG. 2, regardless of how the fundus intensity image isgenerated, in block 230 the fundus intensity image can be displayed. Inthis regard, the fundus intensity image can provide a plurality ofbenefits. First, the display of the fundus intensity image can provideimmediate feedback on scan quality to the operator. Scans contaminatedby eye movements, blinks or other artifacts can be repeated before dataprocessing. Second, because the fundus intensity image is generated fromthe same data as the subsequent 3-D data set, the fundus intensity imagecan provide all necessary landmarks for orienting the 3-D data to otherfundus images, such as fundus photographs and fluorescein angiography.Third, the fundus intensity image serves to locate features that areseen in cross-sectional images.

In block 240, the acquired set of spectral domain scans can be convertedinto a data set that contains the axial (Z-axis) reflectance of thesample. As part of the conversion process, the acquired spectra can betransformed from points linear in wavelength to points linear infrequency (wave number). This transformation can be accomplishedmathematically. Alternatively, the transformation can be accomplished bybuilding a line scan camera that has unequally-spaced pixels.Specifically, the modified line scan camera can incorporate pixelsspaced according to the reciprocal of the distance along the lightdetector chip in the camera. The consequent variation in pixel size willcause variation in pixel gain, but this can be compensatedelectronically or digitally. The transformation would therefore takeplace instantly in hardware, greatly speeding up the generation of thespatial data. The product of the transformation may then be used in theconversion 240 to produce a set of Z-axis intensity information data foreach unique X and Y position of the beam on the sample, i.e. a 3-D dataset. As noted above, this 3-D data can be converted directly into a fullintensity image, for example, by squaring and summing the intensity dataat each X/Y position. The 3-D data is also used to generate conventionalOCT cross-sectional images 185C. The 3-D data can also be subjected to apartial segmentation process (block 250) in order to outline andquantify fluid-filled spaces and other retinal features. This segmenteddata can also be used (block 260), to generate ocular maps, such as“edema maps” and “thickness maps” that can be used for diagnosis andtreatment. The partial segmentation can also be used to generate apartial fundus image. The partial fundus image is generated the same wayas the full fundus image from the 3-D data however, the depth locationand range around that depth is limited and selected through thesegmentation process. As discussed below, a partial fundus image can becreated to highlight certain features or landmarks in the eye. Note thata full segmentation process would be one that identifies many (or all)retinal layers and/or structures. A partial fundus image requiresfinding only one surface, either a specific retinal layer, like theretinal pigment epithelium, or a more general description of retinaltilt and curvature such as the locus of the centroids of each a-scan.

Notably, the retina can be tilted and curved with respect to theCartesian coordinate system of the acquired 3-D data set. Referencesurfaces identified during segmentation can be used as boundaries tocreate a partial intensity image that help identify the tilt andcurvature. The reference surfaces can capture this tilt and curvature asmathematical surfaces within the acquired data set. These referencesurfaces can be generated by combining lines segmented on individuallongitudinal cross sectional scans (B-scans). Reference surfaces alsocan typically correspond to known anatomical layers of the retina.Likely examples include the retinal pigment epithelium (RPE) and theinner limiting membrane (ILM). The reference surfaces can be used tovisualize pathology or to define layers within the data set that havethe variation due to retinal tilt and curvature removed. Data pointswithin these layers can be used to form en face images or partialintensity images that represent retinal structures localized to aparticular depth or anatomic layer.

A characteristic of the data set for the partial fundus intensity imageis that it has thickness, in general greater than the axial resolutionof the OCT. This and the fact that the layer is curved and tilted in away intended to capture anatomy distinguishes it from “C-scans”—thetangential slices produced by SLO/OCT instruments—which areperpendicular to the scanning beam. Hence, C-scans are thin, thethickness being defined by the axial resolution, and they are notusually aligned with retinal structures.

Specifically, intensity in axial scans can be expressed as${{I(\tau)} = {2{\sum\limits_{n}{\sqrt{R_{n}}{\Gamma\lbrack {\tau \pm {2( {\tau_{n} - \tau_{y}} )}} \rbrack}}}}},$where distance along the z-axis is represented by propagation timeτ=nz/c with n the refractive index of tissue and c the speed of light invacuum; τ_(n) and τ_(r) are the propagation times for light reflected bythe nth scatterer in the sample and the reference mirror, respectively;R_(n) is the normalized intensity reflection of the nth scatterer; andsummation is across all axial depths in the sample beam. Γ(τ) is theautocorrelation function of the light source and expresses the axialresolution of the system. Note Γ[τ±2(τ_(n)−τ_(r))] falls rapidly to zeroas (τ_(n)−τ_(r)) becomes greater than the axial resolution. For eachdepth τ, therefore, the reflected intensity comes from only a thin layerof the R_(n).

Thus, a tissue layer defined as above can be expressed by its upperboundary τ₀ (x, y) and lower-boundary τ₁(x, y). The total reflectance ofthe scatterers in the tissue layer at each point (x,y) can be obtainedby squaring${{I(\tau)} = {2{\sum\limits_{n}{\sqrt{R_{n}}{\Gamma\lbrack {\tau \pm {2( {\tau_{n} - \tau_{y}} )}} \rbrack}}}}},$and then summing from τ₀ to τ₁. The result is the desired partial fundusintensity image${F( {x,y} )} = {\sum\limits_{\tau_{0}}^{\tau_{1}}{\{ {2{\sum\limits_{n}{\sqrt{R_{n}}{\Gamma\lbrack {\tau \pm {2( {\tau_{n} - \tau_{y}} )}} \rbrack}}}} \}^{2}.}}$

Still, it is to be understood that the partial fundus intensity image(as well as the fundus intensity image) can be obtained without theexplicit use of the above equation. In fact, any monotonictransformation of the a-line intensities, when summed, can produce anapparent partial fundus intensity image, though the relative intensitiesof the different structures can differ. For example, the squaring stepcan be omitted prior to the summing step and the resulting partialfundus intensity image can suffice. In fact, performing a monotonictransformation, strictly speaking, is not required as a transformationhaving a “little wiggle” can provide a similar result. Notwithstanding,the above equation can provide a true intensity and serves as apreferred example of the technique. Note that the generation of apartial fundus image need not be restricted to a summation between twosurfaces, but could also be defined by an integral under a z-profilethat followed the reference surface, (e.g., the two surface exampledefines a rectangular z-profile).

The partial fundus intensity image can be applied to the registration ofOCT with other modalities. Specifically, in addition to its use fordisplay of pathology, a partial fundus intensity image can be used toprovide high contrast images of the retinal blood vessels that areuseful for aligning the OCT data set to images from other clinicalmodalities (such as fundus photographs). Due to scattering by red bloodcells, major retinal blood vessels cast strong shadows onto theunderlying tissue. By placing one boundary of the slab a distance belowthe ILM that excludes the light scattered by the blood vesselsthemselves, then forming the partial fundus intensity image from alltissue below that boundary, these shadows are emphasized and the bloodvessel pattern stands out in stark relief against the brighter retinalreflection. This type of partial fundus intensity image can be referredto as a shadowgram as other partial fundus intensity images can be usedto emphasize intra-retinal or sub-retinal structures by the reflectedlight of the structures rather than the shadows produced by theincidence of light upon the structures.

The fundus intensity image also solves the specific problem of imageregistration for assessment of the retinal nerve fiber layer in glaucomadiagnosis. In the case of the retinal nerve fiber layer, more accurateregistration will reduce measurement variance and improve the detectionof glaucoma progression.

The method of the present invention can be realized in hardware,software, or a combination of hardware and software. An implementationof the method of the present invention can be realized in a centralizedfashion in one computer system, or in a distributed fashion wheredifferent elements are spread across several interconnected computersystems. Any kind of computer system, or other apparatus adapted forcarrying out the methods described herein, is suited to perform thefunctions described herein.

A typical combination of hardware and software could be a generalpurpose computer system with a computer program that, when being loadedand executed, controls the computer system such that it carries out themethods described herein. The present invention can also be embedded ina computer program product, which comprises all the features enablingthe implementation of the methods described herein, and which, whenloaded in a computer system, is able to carry out these methods.

Computer program or application in the present context means anyexpression, in any language, code or notation, of a set of instructionsintended to cause a system having an information processing capabilityto perform a particular function either directly or after either or bothof the following a) conversion to another language, code or notation; b)reproduction in a different material form. Significantly, this inventioncan be embodied in other specific forms without departing from thespirit or essential attributes thereof, and accordingly, referenceshould be had to the following claims, rather than to the foregoingspecification, as indicating the scope of the invention.

The following references are incorporated herein by reference:

US PATENT DOCUMENTS

U.S. Pat. No. 5,321,501

U.S. Pat. No. 5,459,570

U.S. Pat. No. 5,975,697

U.S. Pat. No. 6,769,769

US20040036838

US20040233457

FOREIGN PATENT DOCUMENTS

CA2390072

WO2004102112

OTHER PUBLICATIONS

-   Bower, B. A. et al. “Rapid Volumetric Imaging of the Human Retina in    vivo Using a Low-Cost, Spectral-Domain Optical Coherence Tomography    System” ARVO annual meeting, May 2, 2005, 8:45 AM-9:00 AM, #1050-   Choma, M. A. et al. (2003). “Sensitivity advantage of swept source    and Fourier domain optical coherence tomography.” Optics Express    11(18): 2183-2189-   de Boer, J. F. et al. “Ultra-High Speed and Ultra-High Resolution    Structural, Flow Velocity, and Polarization Sensitive Sd/Fd-Oct of    the Human Retina” ARVO annual meeting, May 2, 2005, 12:15 PM-12:30    PM, #1116-   Ferguson, R. D. et al. “Enhanced Retinal Imaging With Tracking    Optical Coherence Tomography (TOCT)” ARVO annual meeting, May 2,    2005, 12:45 PM-1:00 PM, #1118-   Fujimoto, J. “Advances in High Resolution and Spectral OCT” Ocular    Imaging 2005, Palm Beach, Fla., Dec. 4, 2005, 11:00 am-   Gregori, G. et al. “3-D OCT Maps of Retinal Pathologies” ARVO annual    meeting, May 2, 2005, 10:00 AM-10:15 AM, #1055-   Hitzenberger, C. K. et al. (2003). “Three-dimensional imaging of the    human retina by high-speed optical coherence tomography.” Optics    Express 11(21): 2753-2761-   Huang, D. et al. (1991). “Optical coherence tomography.” Science    254(5035): 1178-81-   Izatt, J. A. et al. (1993). “Ophthalmic diagnostics using optical    coherence tomography”. Ophthalmic Technologies III, SPIE, 1877:    136-144, Los Angeles, Calif., USA-   Jiao, S., et al. “Simultaneous acquisition of sectional and fundus    ophthalmic images with spectral-domain optical coherence tomography”    Photonics West, Jan. 22, 2005, Ophthalmic Technologies XV, Program #    5688-81.-   Jiao, S. et al. (2005) “Simultaneous acquisition of sectional and    fundus ophthalmic images with spectral-domain optical coherence    tomography” Optics Express 13, 444-452,-   Jiao, S. et al. “Macula Mapping and Simultaneous Acquisition of    Sectional and Fundus Ophthalmic Images With Three-Dimensional    Spectral-Domain Optical Coherence Tomography” ARVO annual meeting,    May 2, 2005, 11:45 AM-12:00 PM, #1114-   Ko, T. H. et al. “Three Dimensional Retinal Imaging of Small Animals    With High-speed, Ultrahigh Resolution Optical Coherence Tomography”    ARVO annual meeting, May 2, 2005, 9:00 AM-9:15 AM, #1051-   Puliafito C. A. “Summary and Significance” American Academy of    Ophthalmology Subspecialty Day on retina, Section X: Ocular Imaging,    New Orleans, Oct. 23, 2004, 3:06 pm-   Sacu, S. et al. “Imaging of Pigment Epithelial Disease Using    Three-dimensional (3D) Ultrahigh Resolution (UHR) Optical Coherence    Tomography (OCT)” ARVO annual meeting, May 3, 2005, 11:15 AM-1:00    PM, # 2563/B116-   Schmidt-Erfurth, U. M. et al. “Three-Dimensional Ultrahigh    Resolution Optical Coherence Tomography (3D UHR OCT): A Video    Presentation” ARVO annual meeting, May 2, 2005, 12:00 PM-12:15 PM,    #1115-   Scholda, C. D. et al. “Visualization of the Vitreoretinal Interface    Using Three-Dimensional Ultrahigh Resolution Optical Coherence    Tomography” ARVO annual meeting, May 2, 2005, 9:45 AM-10:00 AM,    #1054-   Sharp, P. F. et al (2004) “The scanning laser ophthalmoscope a    review of its role in bioscience and medicine” Physics in Medicine    and Biology 49: 1085-1096)-   Srinivasan, V. J. et al. “Intraretinal Thickness Mapping using    Three-Dimensional, High-Speed Ultrahigh Resolution OCT” ARVO annual    meeting, May 2, 2005, 11:30 AM-11:45 AM, #1113-   Swanson, E. A. et al. (1993). “In-vivo retinal imaging by optical    coherence tomography.” Optics Letters 18(21): 1864-1866;-   Werner, J. S. et al. “Three-Dimensional Retinal Imaging With High    Speed and High Resolution OCT” ARVO annual meeting, May 2, 2005,    9:15 AM-9:30 AM, #1052

1. An apparatus for obtaining images of an object comprising: a spectraldomain optical coherence tomography (OCT) system, said system includinga light source, a beam splitter for dividing the light along a samplepath and a reference path, said sample path further including a scannerfor scanning the light in at least one of the X and Y directions overthe sample; a detector for receiving light returned from both the sampleand the reference paths and generating a plurality of sets of outputs,each set corresponding to varying intensities at different wavelengthsof said source at a particular X/Y position of said light on saidsample, said intensities including information about the reflectiondistribution along the sample in the Z axis; and a processor fordirectly converting each set of outputs into a single intensity valuecorresponding to the integrated intensity in the Z axis for theassociated X/Y position of the light on the sample, said singleintensity values being suitable for generating a two dimensional imageintensity map of the object.
 2. An apparatus as recited in claim 1,further including a monitor for displaying the intensity values as a twodimensional intensity map.
 3. An apparatus as recited in claim 1,wherein said processor converts the detector outputs to intensity valuesby one of (a) summing the outputs, (b) squaring and then summing theoutputs, (c) high pass filtering or high pass filtering and thensquaring and summing the results.
 4. An apparatus as recited in claim 1,wherein the two dimensional intensity map is used to register an imageobtained with another imaging modality.
 5. An apparatus as recited inclaim 1, wherein the processor further converts the detector outputsinto a 3-D data set with Z-axis intensity information for each X/Yposition, said 3-D data sets being suitable for generating OCTcross-sectional images.
 6. An apparatus as recited in claim 5, whereinthe two dimensional intensity map is used to register an OCTcross-sectional image.
 7. An apparatus as recited in claim 5, whereinthe intensity map is displayed in parallel with an OCT cross-sectionalimage.
 8. An apparatus as recited in claim 5, wherein the processorfurther functions to segment the 3-D data sets based on landmarks.
 9. Anapparatus as recited in claim 8, wherein the landmarks are identifiedfrom the information generated from the intensity map.
 10. An apparatusas recited in claim 8, wherein the landmarks include a pair of physicalboundaries within the sample.
 11. An apparatus as recited in claim 8,wherein the segmented data is used to generate a partial intensityimage.
 12. An apparatus as recited in claim 8, wherein the segmenteddata is used to generate an ocular map.
 13. An apparatus as recited inclaim 8, wherein the segmented data is used to quantify fluid filledspaces.
 14. An apparatus as recited in claim 1, wherein the light sourceis a broadband light source and the detector is a spectrometer.
 15. Anapparatus as recited in claim 13, wherein the spectrometer includes agrating and a detector array.
 16. An apparatus as recited in claim 1,wherein the source is tunable and swept and intensity at differentwavelengths is obtained over time.
 17. An apparatus for obtaining imagesof an object comprising: a spectral domain optical coherence tomography(SD-OCT) system, said system including a scanner for scanning a lightbeam in at least one of the X and Y directions over the sample, saidsystem being one of a swept source SD-OCT system and a spectrometerbased SD-OCT system, said system generating a plurality of sets ofoutputs, each set corresponding to varying intensities at differentwavelengths of said source at a particular X/Y position of said light onsaid sample, said intensities including information about the reflectiondistribution along the sample in the Z axis; and a processor fordirectly converting each set of outputs into a single intensity valuecorresponding to the integrated intensity in the Z axis for theassociated X/Y position of the light on the sample, said singleintensity values being suitable for generating a two dimensional imageintensity map of the object.
 18. An apparatus as recited in claim 17,further including a monitor for displaying the intensity values as a twodimensional intensity map.
 19. An apparatus as recited in claim 17,wherein said processor converts the detector outputs to intensity valuesby one of (a) summing the outputs, (b) squaring and then summing theoutputs, (c) high pass filtering or high pass filtering and thensquaring and summing the results.
 20. An apparatus as recited in claim17, wherein the light source is a broadband light source and thedetector is a spectrometer.
 21. A method of generating intensity imagesof an object utilizing outputs generated by a spectral domain opticalcoherence tomography (SD-OCT) system, said system including a scannerfor scanning a light beam in at least one of the X and Y directions overthe sample, said system being one of a swept source SD-OCT system and aspectrometer based SD-OCT system, said system generating a plurality ofsets of outputs, each set corresponding to varying intensities atdifferent wavelengths of said source at a particular X/Y position ofsaid light on said sample, said intensities including information aboutthe reflection distribution along the sample in the Z axis, said methodcomprising the steps of: directly converting each set of outputs into asingle intensity value corresponding to the integrated intensity in theZ axis for the associated X/Y position of the light on the sample; andgenerating a two-dimensional intensity map of the integrated intensityvalues.
 22. A method as recited in claim 21, further including the stepof displaying the intensity map on a monitor.
 23. A method as recited inclaim 21, wherein the step of converting outputs into single intensityvalues is performed by one of (a) summing the outputs, (b) squaring andthen summing the outputs, (c) high pass filtering or high pass filteringand then squaring and summing the results.
 24. A method as recited inclaim 21, further including the step of using the two dimensionalintensity map to register an image obtained with another imagingmodality.
 25. A method as recited in claim 21, further including thestep of converting the detector outputs into a 3-D data set with Z-axisintensity information for each X/Y position, said 3-D data sets beingsuitable for generating OCT cross-sectional images.
 26. A method asrecited in claim 25, further including the step of using the twodimensional intensity map to register an OCT cross-sectional image. 27.A method as recited in claim 25, further including the step ofdisplaying the intensity map in parallel with an OCT cross-sectionalimage.
 28. A method as recited in claim 25, further including the stepof segmenting the 3-D data sets based on landmarks.
 29. A method asrecited in claim 25, wherein the landmarks are identified from theinformation generated from the intensity map.
 30. A method as recited inclaim 25, wherein the landmarks include a pair of physical boundarieswithin the sample.
 31. A method as recited in claim 25, wherein thesegmented data is used to generate a partial intensity image.
 32. Amethod as recited in claim 25, wherein the segmented data is used togenerate an ocular map.
 33. A method as recited in claim 25, wherein thesegmented data is used to quantify fluid filled spaces.
 34. An apparatusfor obtaining images of an object comprising: a spectral domain opticalcoherence tomography (OCT) system, said system including a light source,a beam splitter for dividing the light along a sample path and areference path, said sample path further including a scanner forscanning the light in at least one of the X and Y directions over thesample; a detector for receiving light returned from both the sample andthe reference paths and generating a plurality of sets of outputs, eachset corresponding to varying intensities at different wavelengths ofsaid source at a particular X/Y position of said light on said sample,said intensities including information about the reflection distributionalong the sample in the Z axis; and a processor for converting theoutputs of each set of outputs into a 3-D data set including Z-axisintensity information for each X/Y position, said 3-D data sets beingsuitable for generating OCT cross-sectional images, said processorfurther for converting at least some of the 3-D data sets into a singleintensity value corresponding to the integrated intensity across atleast a portion of the Z axis for the associated X/Y position of thelight on the sample, said single intensity values being suitable forgenerating a two dimensional image intensity map of the object.
 35. Anapparatus as recited in claim 34, further including a monitor fordisplaying the intensity values as a two dimensional intensity map. 36.An apparatus as recited in claim 34, wherein the two dimensionalintensity map is used to register an OCT cross-sectional image.
 37. Anapparatus as recited in claim 34, wherein the intensity map is displayedin parallel with an OCT cross-sectional image.
 38. An apparatus asrecited in claim 34, wherein the two dimensional intensity map is usedto register an image obtained with another imaging modality.
 39. Anapparatus as recited in claim 34, wherein the processor furtherfunctions to segment the 3-D data sets based on landmarks.
 40. Anapparatus as recited in claim 39, wherein the landmarks are identifiedfrom the information generated from the intensity map.
 41. An apparatusas recited in claim 39, wherein the landmarks include a pair of physicalboundaries within the sample.
 42. An apparatus as recited in claim 39,wherein the segmented data is used to generate a partial intensityimage.
 43. An apparatus as recited in claim 34, wherein the light sourceis a broadband light source and the detector is a spectrometer.
 44. Anapparatus for obtaining images of an object comprising: a spectraldomain optical coherence tomography (SD-OCT) system, said systemincluding a scanner for scanning a light beam in at least one of the Xand Y directions over the sample, said system being one of a sweptsource SD-OCT system and a spectrometer based SD-OCT system, said systemgenerating a plurality of sets of outputs, each set corresponding tovarying intensities at different wavelengths of said source at aparticular X/Y position of said light on said sample, said intensitiesincluding information about the reflection distribution along the samplein the Z axis; and a processor for converting the outputs of each set ofoutputs into a 3-D data set including Z-axis intensity information foreach X/Y position, said 3-D data sets being suitable for generating OCTcross-sectional images, said processor further for converting at leastsome of the 3-D data sets into a single intensity value corresponding tothe integrated intensity across at least a portion of the Z axis for theassociated X/Y position of the light on the sample, said singleintensity values being suitable for generating a two dimensional imageintensity map of the object.
 45. An apparatus as recited in claim 44,further including a monitor for displaying the intensity values as a twodimensional intensity map.
 46. An apparatus as recited in claim 44,wherein the two dimensional intensity map is used to register an OCTcross-sectional image.
 47. An apparatus as recited in claim 44, whereinthe intensity map is displayed in parallel with an OCT cross-sectionalimage.
 48. An apparatus as recited in claim 44, wherein the twodimensional intensity map is used to register an image obtained withanother imaging modality.
 49. An apparatus as recited in claim 44,wherein the processor further functions to segment the 3-D data setsbased on landmarks.
 50. An apparatus as recited in claim 49, wherein thelandmarks are identified from the information generated from theintensity map.
 51. An apparatus as recited in claim 49, wherein thelandmarks include a pair of physical boundaries within the sample. 52.An apparatus as recited in claim 49, wherein the segmented data is usedto generate a partial intensity image.
 53. An apparatus as recited inclaim 44, wherein the light source is a broadband light source and thedetector is a spectrometer.
 54. A method of generating intensity imagesof an object utilizing the output from a spectral domain opticalcoherence tomography (SD-OCT) system, said system including a scannerfor scanning a light beam in at least one of the X and Y directions overthe sample, said system being one of a swept source SD-OCT system and aspectrometer based SD-OCT system, said system generating a plurality ofsets of outputs, each set corresponding to varying intensities atdifferent wavelengths of said source at a particular X/Y position ofsaid light on said sample, said intensities including information aboutthe reflection distribution along the sample in the Z axis, said methodcomprising the steps of: converting the outputs of each set of outputsinto a 3-D data set including Z-axis intensity information for each X/Yposition, said 3-D data sets being suitable for generating OCTcross-sectional images; converting at least some of the 3-D data setsinto a single intensity value corresponding to the integrated intensityacross at least a portion of the Z axis for the associated X/Y positionof the light on the sample; and generating a two dimensional image mapof the integrated intensity values.
 55. A method as recited in claim 54,further including the step of displaying the intensity map on a monitor.56. A method as recited in claim 54, further including the step of usingthe two dimensional intensity map to register an OCT cross-sectionalimage.
 57. A method as recited in claim 54, further including the stepof displaying the intensity map in parallel with an OCT cross-sectionalimage.
 58. A method as recited in claim 54, further including the stepof using the two dimensional intensity map to register an image obtainedwith another imaging modality.
 59. A method as recited in claim 54,further including the step of segmenting the 3-D data sets based onlandmarks.
 60. A method as recited in claim 59, wherein the landmarksare identified from the information generated from the intensity map.61. A method as recited in claim 59, wherein the landmarks include apair of physical boundaries within the sample.
 62. A method as recitedin claim 59, wherein the segmented data is used to generate a partialintensity image.
 63. An apparatus for obtaining images of an objectcomprising: a spectral domain optical coherence tomography (OCT) system,said system including a broad band light source, a beam splitter fordividing the light along a sample path and a reference path, said samplepath further including a scanner for scanning the light in at least oneof the X and Y directions onto the sample; a detector for receivinglight returned from both the sample and the reference paths, saiddetector including a spectrometer and a line scan camera for generatinga plurality of sets of outputs, each set corresponding to varyingintensities at different wavelengths of said source at a particular X/Yposition of said light on said sample, said intensities includinginformation about the reflection distribution along the sample in the Zaxis, said detector further including an auxiliary detector element formonitoring zero order light and generating an output corresponding tothe integrated intensity in the Z axis for the associated X/Y positionof the light on the sample; and a processor for converting each set ofoutputs from the line scan camera into a 3-D data sets including Z-axisintensity information for each X/Y position, said 3-D data sets beingsuitable for generating cross-sectional images, said processor forconverting the outputs from the auxiliary detector element into a formatsuitable for generating a two dimensional image intensity map of theobject.